PointQ-Bench - Defect Diagnosis: leaderboard
Metric: Sample-level F1 (%) of the multi-label defect diagnosis (which of eight issue types are present; no defect is an empty set), zero-shot over 3,083 point clouds (authentic scans, simulated distortions, AI-generated assets), temperature 0; 2D models see six rendered views, native 3D models 8,192 sampled points; free-form answers mapped to the label space by an LLM parser; higher is better. Source: arxiv.org. Saturation forecast: Around 2032. 14 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-5 (Low) | 42.32 |
| 2 | Qwen 3.5 9B (Non-reasoning) | 39.95 |
| 3 | GPT-5 Mini (Low) | 39.6 |
| 4 | Gemma 3 12B | 37.3 |
| 5 | Claude Haiku 4.5 | 36.88 |
| 6 | Mistral Small 3.2 | 34.3 |
| 7 | Qwen 3.5 27B (Non-reasoning) | 33.87 |
Interactive version: theaggregate.ai/benchmark?slug=pointq-bench-defect-diagnosis · How It Works · Data refreshed daily, snapshot 2026-10-07.